Color reproduction accuracy is a key performance indicator of digital imaging systems, since color is one of the most relevant perceptual attributes that can be attached to an image, be it a photograph or a video clip. Differences in color rendition of images recorded from competing imaging devices like cameras, camcorders or camera phones, are apparent to most users and can result in significant differences in product or perceived brand quality.
In the human visual system, color is a percept, or sensation, deriving from a complex chain of biological processing steps, that starts with the collection of photons radiated from the various surfaces of a scene by means of the eye and provides the visual cortex with a brain map of spectral signatures that represent physical objects under illumination by various light sources.
Studies in vision physiology have long observed and studied the capability of living beings to recognize surfaces under widely varying illumination conditions. The radiation spectra reflected by physical surfaces have a dramatic variation depending on the spectrum of the illuminant they are lit by. Humans, for instance, are very capable in recognizing surfaces under varying lighting conditions, a capability that has been described as “color constancy” in the literature.
Even if humans have this capability, it is more satisfying for the visual perception if the there is only little or no difference between how one perceives a scene in real life and how it appears on an recording of the scene presented for instance on photo paper or a computer screen. Achieving accurate color reproduction in digital imaging systems requires, in a sense, emulating human vision color constancy, that is compensating the effects of the original scene illuminant in such a way that scene surfaces have the correct color appearance in the final image and viewing conditions. We shall indicate this function of a digital imaging system as “color balancing” in the following.
In practical digital imaging systems, the color balancing function is usually implemented by applying an appropriate color space transformation to the digital image color data captured by an imaging sensor. As a consequence of the above described dependency of light spectra reflected by physical surfaces on the spectrum of the illuminant(s), the color space transformation required for proper color rendition also has a significant dependency on the illuminant(s) under which the image is captured. This means that the color balancing parameters must be adapted, either manually or automatically, according to the scene illuminant(s).
The system and method according to the present invention is suitable for determining the scene illuminants by analyzing digital image data, and is therefore especially suitable for determining color balancing parameters, and performing color balancing in a digital imaging system, in such a way that color reproductions are perceived as realistic by observers.
Prior art systems might not reproduce colors in a way resembling what is observed by the eye. This is particularly the case under certain recording conditions, e.g. under certain types of artificial light, or when a scene is dominated by certain types of surfaces, like grass, sky or human skin. In such critical image recording conditions, images of grass, foliage or sky may be less saturated and faces may seem pale or greenish. It is a further object of the present invention to provide an alternative approach
It is an object of the present invention to provide a system and method that in some cases can provide better color balancing than prior art systems.